The Joint Space Operations Center (JSpOC) under U.S. Strategic Command may track up to about 17,000 space objects having diameters greater than 10 cm. With increasing population of space objects, the collision probability between different space objects increases. Ideally, the potential collision of space objects should be predicted in advance in order to guide related space objects maneuver to avoid collision.
To accurately calculate the collision probability and determine the potential collision threats, the status, such as the position, of space objects should be preciously obtained. Unfortunately, due to various perturbations, such as terrestrial gravity, atmospheric drag, multi-body gravitation, solar radiation pressure, tides and spacecraft thrusters, which can affect space object locations. Thus, it is difficult to determine the accurate status of space objects.
The Monte Carlo based algorithm is the benchmark algorithm often used to demonstrate effectiveness of various algorithms for orbit prediction. The Monte Carlo algorithm, however, is rarely used, mainly because it is computational intensive. A Quasi-Monte Carlo (QMC) method is one of the Monte Carlo based algorithms, which is easy to implement and is widely used for collision probability prediction. However, a large number of samples are required to achieve high prediction accuracy.
Thus, there is a need to overcome these and other problems of the prior art and to provide method and system for predicting collision probability of space objects.